MOTIVATION To compare entire genomes from different species, biologists increasingly need alignment methods that are efficient enough to handle long sequences, and accurate enough to correctly align the conserved biological features between distant species. The two main classes of pairwise alignments are global alignment, where one string is transformed into the other, and local alignment, wher...

If we know the structures of the proteins A and B, and the function of protein A, then if we can detect structural similarity between A and B by producing an alignment between them, it can help us infer functionality of B. The problem of protein structure alignment is essentially similar to the sequence alignment; the fact that we have to do structural alignment in 3-d adds to the complexity of...

In this paper a new discriminative word alignment method is presented. This approach models directly the alignment matrix by a conditional random field (CRF) and so no restrictions to the alignments have to be made. Furthermore, it is easy to add features and so all available information can be used. Since the structure of the CRFs can get complex, the inference can only be done approximately a...

We present a new word-alignment approach that learns errors made by existing word alignment systems and corrects them. By adapting transformationbased learning to the problem of word alignment, we project new alignment links from already existing links, using features such as POS tags. We show that our alignment link projection approach yields a significantly lower alignment error rate than tha...

Objective: To develop an algorithm for aligning process traces that considers activity duration during alignment and helps derive data-driven insights from workflow data. Methods: We developed a duration-aware trace alignment algorithm as part of a Java application that provides visualization of the alignment. The relative weight of the activity type vs. activity duration during the alignment i...